جستجوی مقالات مرتبط با کلیدواژه "modeling" در نشریات گروه "پزشکی"

Due to the high volume of the substance in the methyldiethanolamine (MDEA) tanks and the chemical properties, inflammability, and toxicity of the substance as well as the presence of hydrogen sulfide gas in the equipment around this tank, it is important to model its accidents. In this study, the rupture scenario of the MDEA tank in two seasons, cold and hot, with the presence of a protective wall and the absence of a protective wall, was modeled.

At first, the dimensional data of the volume of the tank, the chemical and thermodynamic information of the substance, and the geographic maps of the desired area were defined for the software. Besides, the average weather conditions were inquired from reliable authorities and given to the software so that after performing the calculations, the results of the reservoir rupture scenario would be stated. In this study, the PHAST software was used for calculating the information.

The area under the pool fire radiation in the hot season was 96.5 meters in the wind direction, which was 93 meters in the cold season. Besides, the minimum distance from the center of the fire, where the probability of death is 99%, was 35 meters in the direction of the wind. The concentration of toxic substances up to a distance of 1825 meters in the direction of the wind had a 99% probability of death, and after that it decreased and reached about zero up to a distance of 1865 meters. In the hot season, the pool evaporation rate increased from 1.3 kg/s to 1.6 kg/s. In the cold season, the evaporation rate of substance was 0.3 kg/s. In the absence of a protective wall for a pool fire, the maximum heat radiation was at a distance of 124 meters; this amount of radiation was about 10 meters in the case of the presence of the protective wall.

According to the obtained results, during the occurrence of any of the consequences, which will be in the worst case of these results, the safe distance of the tank can be determined by warning signs. Moreover, in case of accidents, how far the rescue team can approach the danger center and what measures they will have to control the crisis is of great importance.

Cognitive functions play a vital role in how tasks are performed; for this, temporary cognitive and mental dysfunctions could lead to grave consequences, especially when an accurate and prompt response is required. Attention and reaction time to noise are among the most effective exogenous factors on the brain processing mechanism. This study aimed to measure the sustained attention of workers in the steel industry exposed to different sound pressure levels. 

The study was conducted in 4 general stages, including 1- Selecting predictive orientation variables (age, work history, different sound pressure levels); 2- Conducting the Cognitive Performance Test (CPT); 3 Conducting N-BACK Cognitive Performance Test and 4- Modeling cognitive performance changes using model precision methods.

Continuous Performance Test (CPT) results indicated that all three groups’ omission error, commission error, and response time were affected by shift time. All three components increased significantly as the shift ended, decreasing individuals’ cognitive function. Also, the higher noise impact in modeling CPT and N-Back tests indicated reduced workers’ concentration.

These study findings suggested that greater noise weight obtained in test modeling in three-time intervals, i.e., in the beginning, middle, and end of the shift, affected the continuous performance components of the CPT and working memory performance of the N-back test, including workers’ response time and reaction time, with workers’ rate of error increasing and their focus decreasing during the shift.

Considering the importance of positive mental health promotion for preventing psychosocial disorders and increasing physical health and productivity, it is necessary to identify the social determinants of health (SDH) to implement the necessary interventions to improve community health. The present study aims to identify the SDH of positive mental health in Iranian adults.

This is a quantitative and correlational study that was conducted on adults aged 30-60 years living in Tehran, Iran. The sample size was estimated to be 547 people using G*Power software. The samples were selected using a multi-stage random sampling method. After reviewing the literature and meeting with a panel of experts, the SDH list was extracted, and the conceptual model was plotted. The criteria for entering the model was a significance level (P≥0.2). At the end, the structural equation modeling method was applied. The tools used included the mental health continuum–short form, the socioeconomic status questionnaire, multidimensional scale of perceived social support, perceived stress scale-10 items, international physical activity questionnaire-short form, Neissi’s job security questionnaire, Ten Horn’s job security questionnaire, the visual analogue scale for occupational stress assessment, the neighborhood status checklist, Internet use checklist, and social security insurance checklist. The data was analyzed in SPSS software, version 21 and LISREL version 8.8.

The data of 607 questionnaires were analyzed. The mean age of participants was 44.04±9.4 years. The mean score of positive mental health was 45.96±8.65. Among structural determinants, the social class (B=0.181), socio-economic status (B=0.114), job position (B=0.08), building volume per capita (B=0.092) had positive effect on positive mental health, while education (B=-0.071) had negative effect. Among intermediary determinants, job satisfaction (B=0.16), social support (B=0.23) and insurance (B=0.14) had positive effect on positive mental health, while perceived stress (B=-0.62) had negative effect.

Improving socioeconomic status by increasing social support and job satisfaction can increase Iranian adults' positive mental health. On the other hand, the reduction of perceived stress can determine the positive mental health of Iranian adults both directly and indirectly.

Wastewater treatment plants are systems that can contribute to the health of the industry and the environment provided that they function properly. Mathematical and statistical simulators coupled with various models can be used to alleviate the costs of monitoring and managing wastewater treatment systems.

This is a retrospective descriptive- analytical study. Considering the complexity of biological processes along with the advances in data processing methods, algorithms (ANN) and M5 model tree were used in this study in order to make a modelto estimate the effluent COD in the sanitary wastewater treatment plant of one of the country's refineries. ANN and M5 were developed through learning and testing stages based on daily data of five consecutive years (2015-2020). Various statistical indicators such as MSE and R were used to evaluate the models. Ethical considerations were observed in all stages of the study.

In the ANN model with 100 hidden layers, through the training step, the amount of MSE and R respectively decreased and increased, compared to the two modes of 10 and 30 hidden layers. This is why 100 layers were chosen for this model. Also, in the M5 tree model, R-SqOptimal = 0.6147 was calculated by selecting independent data as input, which is significant at the 0.05 level. In other words, with 95% confidence, the developed model is considered sufficiently logical for predicting CODout. The results showed that the ANN model outperformed M5 model tree for predicting effluent COD with a coefficient of determination equal to 0.90 and 0.61, respectively.

Both models have high robustness, reliability and generalizability. Therefore, ANN and M5 model tree data mining techniques can be successfully used for environmental decision-making and estimation of lost data in wastewater treatment plants.

In recent years, some non-invasive methods have been developed to assess the state of health and disease of the skin and tissues. The evaluation of patients by the doctor in terms of skin complications and recovery after laser treatment is done visually and based on experience. Therefore, it is suggested to use quantitative and instrumental methods along with the visual evaluation dependent on the doctor. This research is designed with the aim of providing an optical system based on spectroscopy and the use of mobile phones to investigate the distinction between healthy and unhealthy tissue in order to monitor and investigate the process of skin disease.

Methods & Materials: 

Diffuse reflection spectrometry and spectrum-based imaging methods have been used in this research. Analysis of spectroscopic data from a skin lesion of blood vessels as a study, a spectroscopic imaging method is presented.

spectral data of the skin were analyzed and the difference between the absorption peak of the lesion with healthy skin and the skin with lesion was determined. In the following, using this distinction, the imaging system was proposed based on the results obtained from spectroscopy. This imaging system is a primary optical arrangement to obtain an image without mirror reflection and also to remove environmental factors such as ambient light. In fact, by choosing the index wavelength and lighting the lesion, it is possible to show a better distinction between that lesion and the surrounding healthy area. Also, in this system, a mobile camera is used as a detector.

After recording the image of the lesion and the healthy skin around it simultaneously in one image, image processing and quantification can be used to detect and check tissue changes.

Reliability is always of particular importance in system design and planning; thus, improving reliability is among the approaches for achieving a safe system. Simulation methods are widely used in system reliability assessment. Therefore, this study aims to assess the reliability of the City Gate Gas Station (CGS) using Monte Carlo Simulation (MCS).

This descriptive and analytical study was conducted in one of the CGSs of North Khorasan Province in 2021. The CGS process was carefully examined and its block diagram was plotted. Then, failure time data of CGS equipment were collected over 11 years and time between failures of subsystems was calculated. The failure probability distribution function of subsystems was determined using Easy Fit software and Kolmogorov-Smirnov test. Moreover, subsystems’ reliability was estimated by MCS. Finally, station reliability was calculated considering the series-parallel structure of the CGS.

The results revealed that the failure probability density distribution function of CGS subsystems was based on gamma and normal functions. The reliabilities of filtration, heater, pressure reduction system, and odorize were calculated as 0.97, 0.987, 0.98, and 0.992 respectively, and their failure rates were 0.000003477, 0.0000014937, 0.0000023062, and 0.0000009169 failures per hour respectively. The station reliability was calculated as 0.93.

The failure probability distribution function and reliability assessment of subsystems were determined by data modeling and MCS respectively. Filtration and pressure reduction systems had the highest failure rate and required a proper maintenance program.

Meritocracy is a long-standing desire that is intertwined with the nature of man's God-seeking nature. Every human being in his unconscious and pure nature always has the desire to be worthy, to be in contact with the worthy and to live in a society with a worthy government. In general, the efficiency of any organization depends on the way of management and correct use of its human resources, and a successful organization is able to achieve its goals by using experienced managers. Appointing competent people in suitable positions with their abilities, experiences and capabilities is a process that is reviewed in the form of meritocracy system. Managers need special managerial skills to succeed in the stormy sea of environmental changes. These competencies are not obtained by acquiring professional knowledge and information; Rather, this requires comprehensive development in the dimensions of personal and professional skills and transformation in the attitude and behavior of managers in organizations. Establishing a meritocracy system has countless results and benefits; Strengthening the sense of competitiveness, creating a culture of honoring outstanding and creative experts and employees, creating role models from successful experts, nurturing creative and innovative experts and providing a platform and creating motivation for the emergence of such people, reforming the disordered organizational culture, strengthening organizational solidarity, creating and strengthening occupational and organizational commitment, Strengthening self-confidence in employees, enriching the human capital of the organization. The research method of this article is descriptive analytical method with library technique.

Family functioning is one of the important indicators that guarantee the health and mental health of the family and its members. Therefore, this research aims to provide a prediction model of family function based on brain-behavioral systems in women; The mediating role of primary incompatible schemas was performed with the structural equation modeling approach.

The current research was a descriptive, correlational research based on structural equations. The population studied in this research were all married women who visited cultural centers in the 1st district of Tehran from July to November 2018. 324 married women were selected from the population according to the research variables and using available sampling, and answered the Epstein, Baldwin and Bishop family functioning questionnaires (2003), the short form of Young schema questionnaire (2005), and Carver and White behavioral activation and inhibition system scale (1994). The data were statistically analyzed with SPSS and AMOS software version 21 and using variance inflation factor and tolerance coefficient and a significant level of p<0.05.

Data analysis using structural equation modeling showed that the regression coefficients between behavior inhibition system and family functioning were negatively significant (p<0.01, β=0.167). On the other hand, the total path coefficient between the behavior activating system and family performance was positively significant at the significance level of 0.01 (p<0.01, β=0.262). Also, primary maladaptive schemas negatively predict family functioning (p < 0.01, β= -0.381).

The results showed that the behavioral inhibition system negatively and the behavioral activation system positively and significantly predict family performance. Early maladaptive schemas predict family functioning in female participants.

The assessment of the length of hospital s tay until recovery of patients with Covid-19 and its related factors in different areas can help manage the treatment process and prepare for the epidemic. This s tudy aimed to model the survival time until the recovery of COVID-19 definite patients.

This descriptive-analytical s tudy was retrospective. The s tatis tical population included all COVID-19 definite hospitalized in the educational and medical hospitals of Goles tan University of Medical Sciences from 20 February to 20 July 2020. The outcome variable was discharging confirmed cases of Covid-19. All analytical tes ts and charting were performed in R3.6.2 software.

From a total of 3480 confirmed patients, 77.5% recovered, and 22.5% experienced death at the end of the s tudy or were undergoing treatment. The median length of hospitalization in patients was 6 (IQR: 3-10) days. The mean age of all patients was 52.93±19.20 years; 58.2% of patients were over 49 years old, and half of the population were male. Women infected with Covid-19 survived and recovered 1.16 times more than men. Patients with an age group above 49 years of age had more recovery than their counterparts aged under 49 years.

As evidenced by the obtained results, apart from older adults, the prevalence of the disease needs to be evaluated more closely in young people and men, and these people should be monitored and screened frequently.

 Due to the complexities in the nature of ground water systems, it sounds like a demanding job to model either the time or the location of ground water. However, artificial neural networks have a high capability to model both complicated and non-linear models. Besides, Geostatistic Methods are, to a good extent, accurate in modelling ground water.

 The aim of this study is to simulate groundwater quality parameters (SAR, TDS and EC) of Dezful Andimeshk plain using ANN-PSO and geostatistical models. For this purpose, information from 61 observation wells in Dezful-Andimeshk plain has been used. Neural network model inputs including qualitative parameters SO42- ، pH ، HCO32-، Na+، Mg2+، Ca2+، TDS، SAR and EC were considered.

 The results of simulation with intelligent model showed that the highest accuracy of ANN-PSO model in simulation is related to EC, SAR and TDS parameters, respectively. The results of interpolation by geostatistical method showed that the highest accuracy of Kriging model in simulation is related to EC, TDS and SAR parameters, respectively. The general results obtained from the simulation of groundwater quality parameters showed that the ANN-PSO model is more accurate in simulating the groundwater quality parameters of the plain in Andimeshk than the Kriging model. So that the value of R2 for simulating SAR, TDS and EC parameters using ANN-PSO model in the test phase is 0.92, 0.918 and 0.955 respectively and using kriging model is 0.902. 0.915 and 0.931 were estimated.

 The results of this study also showed that the combination of intelligent models with optimization algorithms is used as a useful tool to simulate groundwater quality parameters.

Not having a suitable planning model is one of the most important barriers to strategic planning in hospitals of Iran. This study aims to design a strategic planning model for hospitals affiliated to Islamic Azad University in Iran.

In this applied study, the review, comparative, quantitative and qualitative methods were used. First, different strategic planning models were collected and, based on them, a conceptual model was designed. Then, a researcher-made questionnaire was designed based on the different dimensions of the model and validated according to a panel of experts. The questionnaire was completed by 30 experts and the results were analyzed using one-way analysis of variance, and the model was finalized by applying the Delphi method.

Regarding the steps of strategic planning, the factors “formation of planning team” (5±0), and “creating the culture and scientific ability for planning in managers and employees” (4.87±0.34) obtained the highest scores. Regarding the implementation steps of the plan, the factors “receiving and implementing the approved plan” (4.87±0.34) and “monitoring of approved plans and their continuous evaluation” (4.87±0.34) had the highest scores. Regarding the strategic planning team members, “hospital manager” (5±0), and “one expert in planning” (4.87±0.46) obtained the highest scores.

The use of the presented strategic planning model based on its implementation steps by a team with the suggested members can improve the stages of developing and implementing plans in hospitals affiliated to Islamic Azad University.